Bibliographic record
Abstract
Based on an investigation of 162 National A-grade tourist attractions and using GIS and some quantitative analysis methods,the spatial structure of tourist attractions in Gansu Province were investigated,with their characteristics and distribution being discussed.Spatial accessibility of tourist attractions was calculated by using cost weight distance method.Then the spatial differences of county accessibility of tourist attractions were discussed by using ESDA.Results show that general scenic spots exhibit an aggregated distribution.Considering the accessibility,we found that the average accessibility is about 68.76 minutes,and the area where the accessibility of scenic spots is within 60 minutes reaches 60%,while the area where the accessibility is within 30 minutes accounts for 22.78% and the longest time needs 396 minutes.Distribution of the accessibility has pointed to traffic line.At county level,the estimated values of Moran's I is positive numbers using analysis of spatial association.All the test results indicate that tourist attractions and adjacent areas show strong positive correlation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".